DESCRIPTION: This is a resubmission of an initial application (1 K23 AG044431) for the Mentored Patient-Oriented Research Career Development Award. The goal of the K23 candidate is to receive training in clinical research design, clinical neuroimaging, and advanced analytic methods, to position her to become an independent clinical researcher focused on early detection of preclinical Alzheimer's disease (AD). Although subjective cognitive concerns (SCC) have often been dismissed as a sign of the worried well, there is emerging evidence to suggest that SCC may herald initial cognitive decrements at the stage of preclinical AD. Recent findings suggest that certain SCC may in fact indicate early awareness prior to objective impairment on standardized tests and may be associated with evidence of early pathology on AD biomarkers. The overarching goal of this project is to understand the dynamic interplay of SCC and objective neuropsychological (NP) measures along the earliest portions of the AD trajectory in order to optimize early detection and predict cognitive decline in the preclinical stages of AD. Self-report of memory decline is very common in older individuals, and there are limited studies of SCC to date that incorporate biomarkers and sensitive measures of objective NP performance in healthy older subjects. Furthermore, a variety of different measures have been utilized leading to discrepant findings in the literature. Based on our preliminary data, we hypothesize that specific SCC will be related to biomarker evidence of AD and subsequent cognitive decline. The candidate is developing a novel measure to improve the discriminability of SCC (D-SCC) that probes the time frame of change, the reference group (self vs. age peers), and items that will best differentiate the ubiquitous complaints associated with the aging process from specific concerns associated with preclinical AD. We plan to associate SCC with objective NP measures, across the spectrum of clinically normal/early Mild Cognitive Impairment. Additionally, we will examine the relationship between SCC and early AD biomarker evidence (amyloid beta (A?) accumulation on PIB-PET amyloid imaging and hippocampal volume) and the ability of SCC to predict longitudinal decline. The proposed research will leverage the rich imaging and clinical dataset available from several ongoing NIA-funded studies, but will provide a unique avenue of investigation for the candidate. The candidate's career development will benefit from close mentorship and scientific guidance from well-established investigators in the Harvard Aging Brain Study (HABS) across multiple disciplines, and will facilitate the candidate's training in advanced statistical analytic techniques and use of neuroimaging data. The findings from this study will inform future secondary prevention trials, in which sensitive indicators of early AD will be necessary to identify high- risk subjects and track early clinical decline.